Surgical Video Research Articles

UNVEILING THE VEIN

Cerebrospinal fluid (CSF)-venous fistula represents a formidable yet often overlooked neurosurgical dilemma. Despite its disabling consequences, it remains significantly underdiagnosed. This abstract sheds light on the clinical intricacies, diagnostic challenges, and therapeutic interventions associated with CSF-venous fistula. Early diagnosis is paramount, yet hindered by its rarity and diverse and often unspecific clinical presentations. The importance of heightened awareness among clinicians and radiologists for timely detection and management cannot be overstated. This presentation will draw upon a review of clinical cases operated in the Royal Hallamshire Hospital, supplemented by a concise surgical video which is focused on surgical technique and benefit of microscope mediated augmented reality.

Spatial-temporal attention for video-based assessment of intraoperative surgical skill

Accurate, unbiased, and reproducible assessment of skill is a vital resource for surgeons throughout their career. The objective in this research is to develop and validate algorithms for video-based assessment of intraoperative surgical skill. Algorithms to classify surgical video into expert or novice categories provide a summative assessment of skill, which is useful for evaluating surgeons at discrete time points in their training or certification of surgeons. Using a spatial-temporal neural network architecture, we tested the hypothesis that explicit supervision of spatial attention supervised by instrument tip locations improves the algorithm’s generalizability to unseen dataset. The best performing model had an area under the receiver operating characteristic curve (AUC) of 0.88. Augmenting the network with supervision of spatial attention improved specificity of its predictions (with small changes in sensitivity and AUC) and led to improved measures of discrimination when tested with unseen dataset. Our findings show that explicit supervision of attention learned from images using instrument tip locations can improve performance of algorithms for objective video-based assessment of surgical skill.

LACOSTE: Exploiting stereo and temporal contexts for surgical instrument segmentation

Surgical instrument segmentation is instrumental to minimally invasive surgeries and related applications. Most previous methods formulate this task as single-frame-based instance segmentation while ignoring the natural temporal and stereo attributes of a surgical video. As a result, these methods are less robust against the appearance variation through temporal motion and view change. In this work, we propose a novel LACOSTE model that exploits Location-Agnostic COntexts in Stereo and TEmporal images for improved surgical instrument segmentation. Leveraging a query-based segmentation model as core, we design three performance-enhancing modules. Firstly, we design a disparity-guided feature propagation module to enhance depth-aware features explicitly. To generalize well for even only a monocular video, we apply a pseudo stereo scheme to generate complementary right images. Secondly, we propose a stereo-temporal set classifier, which aggregates stereo-temporal contexts in a universal way for making a consolidated prediction and mitigates transient failures. Finally, we propose a location-agnostic classifier to decouple the location bias from mask prediction and enhance the feature semantics. We extensively validate our approach on three public surgical video datasets, including two benchmarks from EndoVis Challenges and one real radical prostatectomy surgery dataset GraSP. Experimental results demonstrate the promising performances of our method, which consistently achieves comparable or favorable results with previous state-of-the-art approaches.

High-Risk Biliary Anastomosis During Robotic Pancreaticoduodenectomy: Initial Experience with Biodegradable Biliary Stent

Background and Objectives: Biliary fistulas (BFs) occur in approximately 3–8% of patients undergoing pancreaticoduodenectomy (PD), and the bile duct diameter ≤ 5 mm is the most important risk factor. The aim of this study was to evaluate the efficacy of biodegradable biliary stents (BSs) in reducing complications in patients undergoing robotic pancreaticoduodenectomy (RPD) with a bile duct diameter of ≤5 mm. Materials and Methods: A retrospective single-centre observational study was conducted. Patients undergoing RPD after the completion of the robotic biliary anastomosis learning curve were included in this study. Only patients with a bile duct diameter ≤ 5 mm were included in the analysis. A prospectively held database was used. The intraoperative time for biliary anastomosis was extracted from surgical videos. Results: Of 30 patients, 20 received no biliary stent (nBS) and 10 received a biodegradable stent (BS). The decision to use a stent was based on product availability. The median operative time for biliary anastomosis was significantly shorter in the BS group compared to the nBS group, at 15 min versus 24 min (p < 0.001). Three patients in the nBS group developed a BF, whereas none were observed in the BS group. No stent migration was observed in any of the patients. Conclusions: The use of biodegradable biliary stents in high-risk biliary anastomosis in RPD appears to effectively reduce the incidence of BFs and may serve as a viable strategy to mitigate early biliary complications. The use of biodegradable stents facilitates a faster and easier biliary anastomosis. These findings suggest a potential benefit of using biodegradable stents in complex biliary reconstruction. However, larger studies are needed to confirm these results.

Surgical Educational Video for Identifying Tissue Planes in an Uncomplicated Laparoscopic Hysterectomy

Surgical Educational Video for Identifying Tissue Planes in an Uncomplicated Laparoscopic Hysterectomy

12296 The Use of Surgical Videos to Augment OB/GYN Training in the United States

12296 The Use of Surgical Videos to Augment OB/GYN Training in the United States

Correlation between forceps grasp count and skill proficiency in single-incision laparoscopic percutaneous extraperitoneal closure: A retrospective single-center study.

This study aimed to investigate the correlation between forceps grasp count and procedure time in single-incision laparoscopic percutaneous extraperitoneal closure surgeries and the evolution of these metrics with accumulated experience. We retrospectively reviewed 741 procedures performed by surgeons between 2015 and 2023. Surgical videos were analyzed to calculate the procedure time, defined as the time required for suturing around the hernial orifice, and the forceps grasp count. Correlations were evaluated using Spearman's rank correlation coefficients. Changes in experience were assessed using linear regression. Surgeons demonstrated a significantly longer procedure time (585 s vs. 437 s, p < .001) and higher grasp counts (22 times vs. 17 times, p < .001) for surgeries performed on male patients than on female patients. Grasp count was strongly correlated with procedure time (male patients: r = .800; female patients: r = .758, p < .001). With accumulated experience, both procedure time and grasp count decreased, although novice surgeons showed delayed improvement in forceps manipulation compared with improvement in procedure time. Grasp count was strongly correlated with procedure time in single-incision laparoscopic percutaneous extraperitoneal closure. Accumulated experience improved both metrics, with novice surgeons possibly requiring more time to acquire efficient forceps manipulation skills. Efficient forceps manipulation is a valuable metric for evaluating surgical skills.

Predicting an opaque bubble layer during small-incision lenticule extraction surgery based on deep learning.

This study aimed to predict the formation of OBL during femtosecond laser SMILE surgery by employing deep learning technology. This was a cross-sectional, retrospective study conducted at a university hospital. Surgical videos were randomly divided into a training (3,271 patches, 73.64%), validation (704 patches, 15.85%), and internal verification set (467 patches, 10.51%). An artificial intelligence (AI) model was developed using a SENet-based residual regression deep neural network. Model performance was assessed using the mean absolute error (E MA ), Pearson's correlation coefficient (r), and determination coefficient (R 2 ). Four distinct types of deep neural network models were established. The modified deep residual neural network prediction model with channel attention built on the PyTorch framework demonstrated the best predictive performance. The predicted OBL area values correlated well with the Photoshop-based measurements (E MA = 0.253, r = 0.831, R 2 = 0.676). The ResNet (E MA = 0.259, r = 0.798, R 2 = 0.631) and Vgg19 models (E MA = 0.31, r = 0.758, R 2 = 0.559) both displayed satisfactory predictive performance, while the U-net model (E MA = 0.605, r = 0.331, R 2 = 0.171) performed poorest. We used a panoramic corneal image obtained before the SMILE laser scan to create a unique deep residual neural network prediction model to predict OBL formation during SMILE surgery. This model demonstrated exceptional predictive power, suggesting its clinical applicability across a broad field.

Current application of artificial intelligence in laparoscopic cholecystectomy

Recent advances in artificial intelligence (AI) have sparked a surge in the application of computer vision (CV) in surgical video analysis. Surgical complications often occur due to lapses in judgment and decision-making. In laparoscopic cholecystectomy, achievement of the critical view of safety is commonly advocated to prevent bile duct injuries. However, bile duct injuries rates remain stable, probably due to inconsistent application or a poor understanding of critical view of safety. Advances in AI have made it possible to train algorithms that identify anatomy and interpret the surgical field. AI-based CV techniques may leverage surgical video data to develop real-time automated decision support tools and surgeon training systems. The effectiveness of CV application in surgical procedures is still under early evaluation. The review considers the commonly used deep learning algorithms in CV and describes their usage in detail in four application scenes, including phase recognition, anatomy detection, instrument detection and action recognition in laparoscopic cholecystectomy. The MedLine, Scopus, and IEEE Xplore databases were searched for publications up to 2024. The keywords used in the search were “laparoscopic cholecystectomy”, “artificial intelligence”. The currently described applications of CV in laparoscopic cholecystectomy are limited. Most current research focus on the identification of workflow and anatomical structure, while the identification of instruments and surgical actions is still awaiting further breakthroughs. Future research on the use of CV in laparoscopic cholecystectomy should focus on application in more scenarios, such as surgeon skill assessment and the development of more efficient models.

Evaluation of the Educational Quality of Endonasal Endoscopic Dacryocystorhinostomy Videos on YouTube with IVORY and LAP-VEGaS Guidelines.

Objective: The aim of this study was to evaluate the educational quality of endonasal endoscopic dacryocystorhinostomy (EE-DCR) videos on YouTube with Instructional Videos in Otorhinolaryngology by YO-IFOS (IVORY) and LAParoscopic surgery Video Educational GuidelineS (LAP-VEGaS) guidelines and to evaluate the correlation of the 2 guidelines. Methods: EE-DCR videos were queried using search terms on YouTube. Views, likes, likes/dislikes ratio, age, and length of videos were noted. Videos were evaluated using the IVORY and LAP-VEGaS guidelines. Two IVORY scores were created: total (IVORY-1) and organ-specific (IVORY-2). The correlation analysis between video features and guideline scores was performed. Results: A total of 61 EE-DCR videos were evaluated. The mean score of LAP-VEGaS was 10.3 (±SD 2.7), the mean IVORY-1 score was 22.5 (±SD 5.5), and the mean IVORY-2 score was 10.6 (±SD 1.94). Correlation analysis revealed a statistically significant correlation between the IVORY-1 total score and the number of likes, the duration of the video, the age of the video, and the LAP-VEGaS score. Linear regression analysis showed that higher IVORY-1 scores predicted longer video duration, newer video age, and higher LAP-VEGaS scores. There was a significant association between LAP-VEGaS categories and the IVORY-1 total score (P < .001). Conclusion: The quality of EE-DCR videos is generally low to moderate. The IVORY and LAP-VEGaS guidelines were found to be correlated with each other. Both guidelines can be used to evaluate EE-DCR videos and otolaryngology surgical education videos in general. We believe that scales such as IVORY and LAP-VEGaS may be improved according to specific surgical procedures.

Accuracy of warm ischemia time measurement using a surgical intelligence software in partial nephrectomies: A validation study

AbstractObjectivesThe objectives of this study are to compare the accuracy of warm ischemia times (WITs) derived by a surgical artificial intelligence (AI) software to those documented in surgeon operative reports during partial nephrectomy procedures and to assess the potential of this technology in evaluating postoperative renal function.Patients and methodsA surgical AI software (Theator Inc., Palo Alto, CA) was used to capture and analyse videos of partial nephrectomies performed between October 2023 and April 2024. The platform utilized computer vision algorithms to detect clamp placement and removal, enabling precise WIT measurement. Expert‐reviewed surgical videos served as the ground truth. Platform‐derived WITs were compared to those in surgeon operative reports using paired‐sample t‐tests. Additionally, we analysed the correlation between platform‐derived WITs and postoperative creatinine levels extracted from electronic health records (EHRs) integrated via health level seven (HL7) messaging protocols.ResultsOf 64 eligible cases, 61 were included in the final analysis. Platform‐derived WITs were within 1 min of the ground truth in all procedures, within 30 s in 97%, and within 10 s in over 80%. The mean difference between platform‐derived WITs and ground truth was 8.3 s, significantly lower than the 2.45 min difference for operative reports (p &lt; 0.001). No significant correlation was found between platform‐derived WIT and postoperative creatinine changes, aligning with the view that WIT may not independently determine postoperative renal function. Although not the primary goal of this study, significant correlations were observed between WIT, tumour size and RENAL score.ConclusionThis study demonstrates the high accuracy of a surgical intelligence platform in measuring WIT during partial nephrectomies. The findings support the use of AI‐based surgical time measurement for precise intraoperative documentation and highlight the potential of integrating these data with EHRs to advance research on surgical outcomes.

Deep learning prediction of error and skill in robotic prostatectomy suturing.

Manual objective assessment of skill and errors in minimally invasive surgery have been validated with correlation to surgical expertise and patient outcomes. However, assessment and error annotation can be subjective and are time-consuming processes, often precluding their use. Recent years have seen the development of artificial intelligence models to work towards automating the process to allow reduction of errors and truly objective assessment. This study aimed to validate surgical skill rating and error annotations in suturing gestures to inform the development and evaluation of AI models. SAR-RARP50 open data set was blindly, independently annotated at the gesture level in Robotic-Assisted Radical Prostatectomy (RARP) suturing. Manual objective assessment tools and error annotation methodology, Objective Clinical Human Reliability Analysis (OCHRA), were used as ground truth to train and test vision-based deep learning methods to estimate skill and errors. Analysis included descriptive statistics plus tool validity and reliability. Fifty-four RARP videos (266min) were analysed. Strong/excellent inter-rater reliability (range r = 0.70-0.89, p < 0.001) and very strong correlation (r = 0.92, p < 0.001) between objective assessment tools was demonstrated. Skill estimation of OSATS and M-GEARS had a Spearman's Correlation Coefficient 0.37 and 0.36, respectively, with normalised mean absolute error representing a prediction error of 17.92% (inverted "accuracy" 82.08%) and 20.6% (inverted "accuracy" 79.4%) respectively. The best performing models in error prediction achieved mean absolute precision of 37.14%, area under the curve 65.10% and Macro-F1 58.97%. This is the first study to employ detailed error detection methodology and deep learning models within real robotic surgical video. This benchmark evaluation of AI models sets a foundation and promising approach for future advancements in automated technical skill assessment.

Deep learning-based surgical step recognition for laparoscopic right-sided colectomy.

Understanding the complex anatomy and surgical steps involved in laparoscopic right-sided colectomy (LAP-RC) is essential for standardizing the surgical procedure. Deep-learning (DL)-based computer vision can achieve this. This study aimed to develop a step recognition model for LAP-RC using a dataset of surgical videos with annotated step information and evaluate its recognition performance. This single-center retrospective study utilized a video dataset of laparoscopic ileocecal resection (LAP-ICR) and laparoscopic right-sided hemicolectomy (LAP-RHC) for right-sided colon cancer performed between January 2018 and March 2022. The videos were split into still images, which were divided into training, validation, and test sets using 66%, 17%, and 17% of the data, respectively. Videos were manually classified into eight main steps: 1) medial mobilization, 2) central vascular ligation, 3) dissection of the superior mesenteric vein, 4) retroperitoneal mobilization, 5) lateral mobilization, 6) cranial mobilization, 7) mesocolon resection, and 8) intracorporeal anastomosis. In a simpler version, consecutive surgical steps were combined, resulting in five steps. Precision, recall, F1 scores, and overall accuracy were assessed to evaluate the model's performance in the surgical step classification task. Seventy-eight patients were included; LAP-ICR and LAP-RHC were performed in 35 (44%) and 44 (56%) patients, respectively. The overall accuracy was 72.1% and 82.9% for the eight-step and combined five-step classification tasks, respectively. The automatic surgical step-recognition model for LAP-RCs, developed using a DL algorithm, exhibited a fairly high classification performance. A model that understands the complex steps of LAP-RC will aid the standardization of the surgical procedure.

Refining delivery and positioning: A modified approach to FIL SSF intraocular lens implantation using the "full reverse" technique.

To present a modified surgical technique for implantation of the sutureless scleral-fixated hydrophilic intraocular lens (FIL SSF). Single surgeon retrospective case series and review of surgical videos with step-by-step technique analysis. Uncorrected and best corrected visual acuity (UCVA and BCVA), refractive error (spherical equivalent), full clinical examination with intraocular pressure (IOP) measurement, endothelial cell density on corneal specular microscopy and macular optical coherence tomography (OCT) were recorded at baseline, 1, 4 and 8 weeks postoperatively. The FIL SSF IOLs were successfully implanted using the so-called "full reverse" technique, having the lens loaded in the injector in an upside-down fashion, as opposed to IOL technical specifications. In all cases, the FIL SSF IOL was properly placed in the ciliary sulcus, well-centered and without signs of tilt. Follow up figures at 2 months are consistent with published data, confirming the potential benefits of the new implantation technique. In our preliminary experience, the "full reverse" technique of the FIL SSF IOL has proven effective in preventing incorrect IOL orientation in 100% of cases. However, larger prospective controlled studies and longer follow up are required to either support or disprove our results.

Assessing the Role of Artificial Intelligence in the Creation of Patient Educational Videos for Corneal Refractive Surgery.

We aim to assess the ability of artificial intelligence (AI) to generate patient educational videos for various corneal refractive surgeries. Three AI text-to-video platforms (InVideo (San Francisco, CA), ClipTalk (San Francisco, CA), and EasyVid (Los Angeles, CA)) were used to create patient educational videos for laser-assisted in situ keratomileusis (LASIK), photorefractive keratectomy (PRK), and small incision lenticule extraction (SMILE), respectively. Videos for LASIK and PRK from the American Academy of Ophthalmology (AAO) and a SMILE video from Zeiss served as controls for each surgery. A three-point grading system (from zero to three, with zero being the worst and three being the best in each category) was used to compare videos in terms of "image accuracy," "script accuracy," "image clarity," and "script alignment." In terms of image accuracy, the control videos outperformed InVideo, EasyVid, and ClipTalk for LASIK (3 versus 0.667 versus 0 versus 0; p<0.005), PRK (3 versus 1 versus 0.33 versus 0; p<0.05 for InVideo, p<0.005 all), and SMILE (3 versus 0.33 versus 0 versus 0.33; p<0.005), respectively. With a few exceptions, all three AI models performed similarly to the control videos in terms of script accuracy, image clarity, and script alignment. In their current state, AI text-to-video generators can produce surgical educational videos for patients with accurate script narration and high image clarity, although these platforms are not yet capable of producing medically accurate images to go along with these scripts. Further improvements in the medical accuracy of these images must be made to make these videos more appropriate for patient consumption.

Finger-Controlled Nonultrasonic Lens Extractor.

To report initial surgical experience and learning curve with a novel finger-controlled, ultrasoundless lens extractor device and provide insights for future surgical endeavors. Bascom Palmer Eye Institute (Miami, FL). Single-center, non-comparative, retrospective, consecutive case series. 61 eyes of 51 individuals with cataract. All surgeries were performed with the miCOR® 700 lens extractor (Carl Zeiss Meditec Inc, Dublin, CA) by a single experienced physician. Nuclear density was graded preoperatively. Corrected distance visual acuity (CDVA), intraocular pressure (IOP) and pachymetry were evaluated pre- and postoperatively. Surgical videos were reviewed to collect data on time for each surgical step and complications. Regression analyses assessed the learning curve, performance improvement and effects of nuclear density on surgical time and postoperative pachymetric variation. Subjects had a mean age of 72.2 ± 7.6 years. Increased surgical experience significantly reduced procedure time (P < 0.001), nuclear removal time (P = 0.018) and cortex removal time (P = 0.002). Higher nuclear density resulted in longer procedure (P < 0.001) and nuclear removal time (P < 0.001). One posterior capsular rent occurred, not attributed to the lens extractor. No thermal damage to the corneal wound was observed. Postoperative CDVA improved significantly (P < 0.001 for eyes without ocular comorbidities, P = 0.016 for eyes with ocular comorbidities). All cases of corneal edema and IOP spikes resolved within a month. The miCOR® 700 lens extractor offers an innovative, cost-effective approach to cataract surgery. Further research is needed to compare it with conventional phacoemulsification techniques.

Assessing anatomical variations of the superior mesenteric artery via three-dimensional CT angiography and laparoscopic right hemicolectomy: a retrospective observational study.

This study aimed to analyse the anatomical relationships and differences between the superior mesenteric vessels and their branches by reviewing a laparoscopic right hemicolectomy surgery video and comparing it with preoperative three-dimensional computed tomography (3D-CT) angiography and to verify the accuracy of 3D-CT vascular reconstruction techniques. Surgical videos and preoperative imaging data of 52 patients undergoing laparoscopic right hemicolectomy were analysed to observe and summarize the probability of occurrence and adjacency of superior mesenteric vascular branches, and the lengths of specific sites of their branches were measured using the above two methods. Preoperative CT images and surgical video showed that the ileocolic artery (ICA) was present in 98.1% (51/52) and the ileocolic vein (ICV) was present in 100% (52/52), and ICA was present in 13.7% (7/51) of the ICV directly anteriorly, 13.7% (7/51) anteriorly superiorly, 3.9% (2/51) anteriorly inferiorly, 11.8% (6/51) directly posteriorly, 37.2% (19/51) post superiorly, and 19.7% (10/51) posteriorly inferiorly. In the surgical video, the probability of presence of the right colic artery (RCA) was 21.2% (11/52). On CT images, the RCA was present in 10 patients. The length of the origin of the middle colic artery (MCA) from its bifurcations was 2.33 ± 0.87 cm measured intraoperatively using a sterile isometric filament, and the length measured using 3D-CT vascular reconstruction was 2.36 ± 0.91 cm; the difference was not statistically significant (P = 0.348). The length of the MCA and ICA initiation points was 3.22 ± 0.75 cm measured intraoperatively using sterile isometric filaments and 3.36 ± 0.72 cm measured using 3D-CT vascular reconstruction, which was a statistically significant difference (P < 0.001). 3D-CT vascular reconstruction can accurately predict the vessels related to right hemicolectomy in most cases. It is an important method for preoperative prediction of superior mesenteric vessels, which can guide surgeons in the intraoperative vessel identification.

LoViT: Long Video Transformer for surgical phase recognition

Online surgical phase recognition plays a significant role towards building contextual tools that could quantify performance and oversee the execution of surgical workflows. Current approaches are limited since they train spatial feature extractors using frame-level supervision that could lead to incorrect predictions due to similar frames appearing at different phases, and poorly fuse local and global features due to computational constraints which can affect the analysis of long videos commonly encountered in surgical interventions. In this paper, we present a two-stage method, called Long Video Transformer (LoViT), emphasizing the development of a temporally-rich spatial feature extractor and a phase transition map. The temporally-rich spatial feature extractor is designed to capture critical temporal information within the surgical video frames. The phase transition map provides essential insights into the dynamic transitions between different surgical phases. LoViT combines these innovations with a multiscale temporal aggregator consisting of two cascaded L-Trans modules based on self-attention, followed by a G-Informer module based on ProbSparse self-attention for processing global temporal information. The multi-scale temporal head then leverages the temporally-rich spatial features and phase transition map to classify surgical phases using phase transition-aware supervision. Our approach outperforms state-of-the-art methods on the Cholec80 and AutoLaparo datasets consistently. Compared to Trans-SVNet, LoViT achieves a 2.4 pp (percentage point) improvement in video-level accuracy on Cholec80 and a 3.1 pp improvement on AutoLaparo. Our results demonstrate the effectiveness of our approach in achieving state-of-the-art performance of surgical phase recognition on two datasets of different surgical procedures and temporal sequencing characteristics. The project page is available at https://github.com/MRUIL/LoViT.

Clinical application of inferior pancreaticoduodenal artery management in laparoscopic pancreaticoduodenectomy

Objective: To investigate the clinical effect of proper management of inferior pancreaticoduodenal artery (IPDA) in laparoscopic pancreaticoduodenectomy (LPD). Methods: This is a retrospective case series study. The clinical and pathological data of 70 patients who received LPD due to pancreatic head tumors, periampullary tumors, or distal common bile duct tumors in the Pancreatic Center of the Second Clinical College of Guangzhou University of Chinese Medicine from January to December 2022 were retrospectively collected. There were 47 males(67.1%) and 23 females(32.9%),aged (59.9±12.8)years(range:13 to 87 years).The procedure of IPDA exposure was as follows:a middle approach was utilized to expose the right half of superior mesenteric artery(SMA) and its right branches between the SMA and superior mesenteric vein(SMV) in superior colonic region. In the subcolonic region,SMA trunk exposure via dissection along the jejunal artery from feet to head and identification the association between IPDA and jejunal artery were prior to IPDA root ligation and dissection. The safety and efficacy of intraoperative IPDA handling were assessed based on surgical videos. Follow-up was carried out in outpatient clinic or by telephone, and outpatient follow-up was conducted once every 1 to 3 months after surgery. Results: The percentage of total LPD was 98.6%(69/70),with all patients achieving R0 resection. Nine cases(12.9%) were involved in combined vascular resection and reconstruction,with 1 case (1.4%) requiring additional upper abdominal incision for vascular and gastrointestinal reconstruction,while the remaining eight cases (11.4%) were completed laparoscopically. The operative time was (432.7±115.4)minutes(range:282 to 727 minutes), and the blood loss was (140.0±125.7)ml(range:20 to 800 ml). Only two patients(2.9%) received fresh frozen plasma transfusion,with an average volume of 650 ml. Reliable ligation and safe handling of the IPDA were achieved in 91.4%(64/70) of cases, with 8.6%(6/70) suffering from IPDA injury-related bleeding. No one was converted to opened surgery. Pathologically,the mean tumor size was (3.3±1.6)cm (range:1 to 7 cm),and the mean number of harvested lymph nodes was 17.0±7.3(range:0 to 46). Lymph node metastasis was observed in 13 cases (18.6%). Five cases (13.2%) developed grade B pancreatic fistula,while no grade C pancreatic fistula occurred. Other complications included bile leakage in one case(1.4%),delayed gastric emptying in two cases(2.9%), lymphatic leakage in 2 cases(2.9%),intra-abdominal infection in 9 cases(12.9%),and fat liquefaction of surgical incision in 1 case(1.4%). Two cases(2.9%) experienced postoperative intra-abdominal bleeding,one due to mesangial bleeding of lesser curvature of the stomach and the other due to oozing from the hepatic arterial sheath. These bleeding events were not concerned with IPDA. The average length of postoperative hospital stay was (15.2±4.6)days(range:9 to 28 days). Conclusion: Proper intraoperative management of IPDA in LPD might reduce IPDA-related bleeding during and after surgery and improve the safety of LPD.

Development and dissemination of a series of surgical skills and procedures video tutorials using a novel, low-cost, and sustainable simulation kit (GlobalSurgBox)

IntroductionSurgical simulation and video-based learning are limited in lower-resource settings. We sought to develop and assess a series of surgical tutorials using a low-cost simulator. MethodsWe created 8 surgical skills and procedures videos using low-cost equipment. We assessed video quality using the DISCERN scale and the Global Quality Scale (GQS). ResultsVideos ranged from surgical techniques to complex procedures. We uploaded these to Youtube and included them in the curriculum of a medical school in Rwanda. Excluding the cost of the kit (25 USD), production costs ranged from 2 to 5 USD. All videos scored a mean DISCERN of 2.44 ​± ​1.05 and GQS of 3.06 ​± ​0.90. Generally, these lacked points on providing additional sources of information and addressing areas of uncertainty. ConclusionsThis study addresses the demand for accessible surgical education resources. Using low-cost, standardized materials ensures consistency, democratization of training, and feasibility.